Open Access
Issue
E3S Web Conf.
Volume 353, 2022
8th International Conference on Energy and City of the Future (EVF’2021)
Article Number 03004
Number of page(s) 14
Section Materials & Factories of the Future
DOI https://doi.org/10.1051/e3sconf/202235303004
Published online 29 June 2022
  1. Z. Rajnai, I. Kocsis, Labor market risks of Industry 4.0, digitization, robots and AI, in Proceedings of the 15th IEEE International Symposium on Intelligent Systems and Informatics, IEEE (2017) [Google Scholar]
  2. G. D. Putnik, V. Shah, Z. Putnik, L. Ferreira, Machine Learning in Cyber-Physical Systems and manufacturing singularity-it does not mean total automation, human is still in the centre: Part II: In-CPS and a view from community on Industry 4.0 impact on society, Journal of Machine Engineering, 21, 133–153 (2021) [CrossRef] [Google Scholar]
  3. S. Nahavandi, Industry 5.0—A human-centric solution. Sustainability, 11(16), 4371 (2019) [CrossRef] [Google Scholar]
  4. F. Longo, A. Padovano, S. Umbrello, Value-Oriented and Ethical Technology Engineering in Industry 5.0: A Human-Centric Perspective for the Design of the Factory of the Future, Applied Sciences, 10(12), 4182 (2020) [CrossRef] [Google Scholar]
  5. A. Bruzzone, M. Massei, K. Sinelshnkov, Enabling strategic decisions for the industry of tomorrow, Procedia Manufacturing, 42, 548–553 (2020) [CrossRef] [Google Scholar]
  6. C. P. Gonçalves, Cyberspace and Artificial Intelligence: The New Face of Cyber-Enhanced Hybrid Threats, in Cyberspace, IntechOpen (2019) [Google Scholar]
  7. V. Terziyan, M. Golovianko, S. Gryshko, Industry 4.0 Intelligence under Attack: From Cognitive Hack to Data Poisoning, in Cyber Defence in Industry 4.0 Systems and Related Logistics and IT Infrastructure, NATO Science for Peace and Security Series D: Information and Communication Security, 51, 110–125, (2018) [Google Scholar]
  8. I. J. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, … Y. Bengio, Generative adversarial networks, arXiv preprint arXiv:1406.2661 (2014) [Google Scholar]
  9. V. Terziyan, S. Gryshko, M. Golovianko, Patented Intelligence: Cloning Human Decision Models for Industry 4.0. Journal of Manufacturing Systems, 48, 204–217, (2018) [CrossRef] [Google Scholar]
  10. V. Terziyan, A. Nikulin, Semantics of Voids within Data: Ignorance-Aware Machine Learning, ISPRS International Journal of Geo-Information, 10(4), 246 (2021) [CrossRef] [Google Scholar]
  11. M. Gavriushenko, O. Kaikova, V. Terziyan, Bridging Human and Machine Learning for the Needs of Collective Intelligence Development, Procedia Manufacturing, 42, 302–306 (2020) [CrossRef] [Google Scholar]
  12. V. Terziyan, M. Gavriushenko, A. Girka, A. Gontarenko, O. Kaikova, Cloning and Training Collective Intelligence with Generative Adversarial Networks, IET Collaborative Intelligent Manufacturing, 3(1), 64–74 (2021) [CrossRef] [Google Scholar]
  13. A. Girka, V. Terziyan, M. Gavriushenko, A. Gontarenko, Anonymization as Homeomorphic data Space Transformation for Privacy-Preserving Deep Learning, Procedia Computer Science, 180, 867–876 (2021) [CrossRef] [Google Scholar]
  14. V. Terziyan, O. Kaikova, Neural Networks with Disabilities: An Introduction to Complementary Artificial Intelligence, Neural Computation, 34(1), 255–290 (2021) [PubMed] [Google Scholar]
  15. V. Terziyan, S. Gryshko, M. Golovianko, Taxonomy of Generative Adversarial Networks for Digital Immunity of Industry 4.0 Systems, Procedia Computer Science, 180, 676–685 (2021) [CrossRef] [Google Scholar]
  16. M. Golovianko, S. Gryshko, V. Terziyan, T. Tuunanen, Towards Digital Cognitive Clones for the Decision-Makers: Adversarial Training Experiments, Procedia Computer Science, 180, 180–189 (2021) [CrossRef] [Google Scholar]
  17. V. Branytskyi, M. Golovianko, S. Gryshko, D. Malyk, V. Terziyan, T. Tuunanen, Digital Clones and Digital Immunity: Adversarial Training Handles Both, International Journal of Simulation and Process Modelling (to be published, 2022) [Google Scholar]
  18. V. Semenets, V. Terziyan, S. Gryshko, M. Golovianko, Assessment and Decision-Making in Universities: Analytics of the Administration-Staff Compromises, arXiv preprint arXiv:2105.10560 (2021) [Google Scholar]
  19. V. Semenets, S. Gryshko, M. Golovianko, O. Shevchenko, L. Titova, O. Kaikova, V. Terziyan, T. Tiihonen, How the University Portal Inspired Changes in the Academic Assessment Culture, arXiv preprint arXiv:2105.14154 (2021) [Google Scholar]
  20. S. Kumpulainen, V. Terziyan, Artificial General Intelligence vs. Industry 4.0: Do They Need Each Other?, Procedia Computer Science (to be published, 2022) [Google Scholar]
  21. V. Terziyan, O. Vitko, Explainable AI for Industry 4.0: Semantic Representation of Deep Learning Models, Procedia Computer Science (to be published, 2022) [Google Scholar]
  22. V. Branytskyi, M. Golovianko, D. Malyk, V. Terziyan, Generative Adversarial Networks with Bio-Inspired Primary Visual Cortex for Industry 4.0, Procedia Computer Science (to be published, 2022) [Google Scholar]
  23. V. Terziyan, M. Golovianko, O. Shevchenko, Semantic Portal as a Tool for Structural Reform of the Ukrainian Educational System, Information Technology for Development, 21(3), 381–402 (2015) [CrossRef] [Google Scholar]

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